理论(学习稳定性)
遗传算法
全局优化
锂(药物)
分类
经济
计算机科学
国际贸易
算法
医学
机器学习
内分泌学
作者
Congcong Wu,Xiangyun Gao,Xian Xi,Yiran Zhao,Li Yu
标识
DOI:10.1016/j.resourpol.2021.102336
摘要
The international mineral resources trade is an important way to correct the unbalanced distribution of global mineral resources. This paper proposes a bi-objective model to improve the stability of the mineral resource trade by optimizing the trade structure. The improved nondominated sorting genetic algorithm (NSGA-II) was used to solve the bi-objective optimization model, and a more robust trade structure was obtained. We applied the model to the optimization of the global lithium carbonate trade. The optimized results enabled us to identify the key trade relationships that play the most critical role in improving the stability of lithium carbonate trade. The effectiveness of the optimization model was proved by analyzing the stability of major net importing countries and the influence of major net exporting countries. Furthermore, the strongest destructive model, which was opposite to the optimal model, was used to analyze the core trade relations and core countries in the actual lithium trade. These core trade relations provide a foundation for maintaining the stability of the international trade. Our work provides new ideas for improving the stability of the global mineral trade and provides a new perspective and special basis for trading countries to choose trade partners.
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